The fusion-minimization problem for photonic graph states is formalized as minimum trail cover; most bounded variants are NP-hard, but heuristics plus a TSP reduction give near-optimal fusion counts in benchmarks.
Deterministic and reconfigurable graph state generation with a single solid-state quantum emitter
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abstract
Measurement-based quantum computing offers a promising route towards scalable, universal photonic quantum computation. This approach relies on the deterministic and efficient generation of photonic graph states in which many photons are mutually entangled with various topologies. Recently, deterministic sources of graph states have been demonstrated with quantum emitters in both the optical and microwave domains. In this work, we demonstrate deterministic and reconfigurable graph state generation with optical solid-state integrated quantum emitters. Specifically, we use a single semiconductor quantum dot in a cavity to generate caterpillar graph states, the most general type of graph state that can be produced with a single emitter. By using fast detuned optical pulses, we achieve full control over the spin state, enabling us to vary the entanglement topology at will. We perform quantum state tomography of two successive photons, measuring Bell state fidelities up to 0.80$\pm$0.04 and concurrences up to 0.69$\pm$0.09, while maintaining high photon indistinguishability. This simple optical scheme, compatible with commercially available quantum dot-based single photon sources, brings us a step closer to fault-tolerant quantum computing with spins and photons.
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Finding trail covers: near-optimal decompositions of graph states as linear fusion networks
The fusion-minimization problem for photonic graph states is formalized as minimum trail cover; most bounded variants are NP-hard, but heuristics plus a TSP reduction give near-optimal fusion counts in benchmarks.